Risk-based allocation of COVID-19 personal protective equipment under supply shortages

被引:5
|
作者
Baloch, Gohram [1 ]
Gzara, Fatma [2 ]
Elhedhli, Samir [2 ]
机构
[1] Simon Fraser Univ, Beedie Sch Business, Burnaby, BC, Canada
[2] Univ Waterloo, Dept Management Sci, Waterloo, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
OR in health services; COVID-19 PPE allocation; Infection risk; Distribution planning; WHO ethical considerations; RESOURCE-ALLOCATION; EPIDEMIC; MODEL;
D O I
10.1016/j.ejor.2023.04.001
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The COVID-19 outbreak put healthcare systems across the globe under immense pressure to meet the un-precedented demand for critical supplies and personal protective equipment (PPE). The traditional cost-effective supply chain paradigm failed to respond to the increased demand, putting healthcare workers (HCW) at a much higher infection risk relative to the general population. Recognizing PPE shortages and high infection risk for HCWs, the World Health Organization (WHO) recommends allocations based on ethical principles. In this paper, we model the infection risk for HCWs as a function of usage and use it as the basis for distribution planning that balances government procurement decisions, hospitals' PPE usage policies, and WHO ethical allocation guidelines. We propose an infection risk model that integrates PPE allocation decisions with disease progression estimates to quantify infection risk among HCWs. The proposed risk function is used to derive closed-form allocation decisions under WHO ethical guidelines in both deterministic and stochastic settings. The modelling is then extended to dynamic distribution planning. Although nonlinear, we reformulate the resulting model to make it solvable using off-the-shelf software. The risk function successfully accounts for virus prevalence in space and in time and leads to allocations that are sensitive to the differences between regions. Comparative analysis shows that the allocation policies lead to significantly different levels of infection risk, especially under high virus preva-lence. The best-outcome allocation policy that aims to minimize the total infected cases outperforms other policies under this objective and that of minimizing the maximum number of infections per pe-riod. & COPY; 2023 Elsevier B.V. All rights reserved.
引用
收藏
页码:1085 / 1100
页数:16
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